• Interpretative language (no compilation needed)
• No manual memory management
• Vectorized

• Widely used, vast community of R users
• Good life expectancy

• Open-source: anyone can see/create/modify
• Multiplatform: Windows, Mac, Unix… It works everywhere

• More and more packages
• More and more popular among data scientists and (now) biologists

• vector: Ordered collection of elements of the same type

• list: Flexible container, mixed type possible. Recursive

• matrix: Table of elements of the same type

• data.frame: Table of mixed type elements

Try to raise errors using operators.

• c() Concatenate function
• 1:10 Vector with numbers from 1 to 10

• c() Concatenate function
• 1:10 Vector with numbers from 1 to 10

• Create a vector with 7 numeric values
• Create a vector with 7 character values

Using index/position between []

• length() Number of elements in the vector
• names() Get or set the names of the vector’s value

• sort() Sort a vector
• sample() Shuffle a vector
• rev() Reverse a vector

• head()/tail() Print the first/last values
• summary() Summary statistics
• min()/max()/mean()/median()/var() Minimum, maximum, average, median, variance
• sum Sum of the vector’s values

• Simple arithmetic operations over all the values of the vector
• Or values by values when using vectors of same length
• Arithmetic operations: +, -, *, /
• Other exist but let’s forget about them for now

• There are three basic types of objects: numeric, character and boolean
• Basic objects can be combined into more complex objects, such as vectors, lists, matrices and data.frames
• Objects need to be ‘stored’ in variables so they can be easily retrieved and modified
• Basic and complex numeric objects can handle arithmetic operations
• Functions can be applied to basic and/or complex objects depending on the type of data they are designed to process

• A vector is a sequence of elements that are all of the same type
• There are multiple ways to create it
• [] are used to manipulate elements of a vector
• Numeric vectors support arithmetic operations
• Elements in a vector can be named
• Various functions can be used with vectors to modify or summarize them

• Apply a function to each row (or column) of a matrix
• No manual iteration, the loop is implicit
• Second parameter: 1 means row and 2 means columns

To tell R where to find your data, you need to specify the path to the file. There are two types of paths for the same file:

• Absolute Path: This is the full path to the file, which you can see in the address bar when you are in a folder.
• Relative Path: This describes how to navigate from one folder to another to reach the file.

Paths are always enclosed in double quotes (").

Change the directory where R is working

``

• What data structure is more appropriate? vector, matrix?
• Does R read/write the file the way you want?
• The extra parameters of the functions are your allies

To read a data.frame from a multi-column file

• file=the path to the file
• header= Set to TRUE if the 1st line correspond to column names
• as.is= Set to TRUE to read the values as simple type, recommended
• sep= The character that separate the columns, e.g. , or \t (tabs)
• row.names= The column number to use as row names ``

To write a data.frame in a multi-column file

• df the data.frame to write
• file= the file name
• col.names= TRUE print the column names in the first line
• row.names= TRUE print the row names in the first columns
• quote= TRUE surround character by double quotes
• sep= the character that separates each column. ’ ’ by default.

Plot the value distribution of a vector. x The vector with the values to plot

Plot one vector against the other. x The first vector to plot (x-axis) y The second vector to plot (y-axis) type How the points are plotted. “p” for points, “l” for points joined by lines

Plot the distribution of variables. x The matrix of distributions

col= The colour of the points/lines
pch= The shape of the points lty= The shape of the lines

lines() Same as plot but super-imposed to the existent one abline() Draw a vertical/horizontal line

Generate plots for: 1. a boxplot of columns 1 to 10. 2. the distribution of the median gene expression. Add a vertical dotted ine to mark their average value. 3. the distribution of the median sample expression. If any visual outlier, remove it and check the distribution again. 4. the expression of gene 333 againt gene 666. Surimpose in red triangles the expression of gene 333 against gene 667.

TRUE / FALSE values

Test a condition. If TRUE, runs some instructions. If FALSE, runs something else or nothing.

if( Condition ){
... Instructions
}

Write a if block that automatically classify the expression of the first gene into: - ‘high’ if its maximum value is higher than 4 - ‘low’ if not

• Start with function() to define a function
• All the objects created within the function are temporary
• return() specifies what will be returned by the function

Create a function that classify the average value of a vector. It returns: - small if the average is below 3 - medium if the average is between 3 and 7 - high if the average is above 7 Test your function on vectors with random numbers from 0 to 10.

Create a function that: 1. returns the average of the minimum and maximum value of a vector 2. returns how many values are higher than 3 in a vector Test your function on vectors with random numbers from 0 to 10.

Use your functions on all mat.gene data frame

Iterates over the elements of an iterator and runs intructions.

for(v in vec){
... Instruction
}

Runs instructions as long as a condition is TRUE.

while( CONDITION ){
... Instruction
}

Write a function that computes the mean values of the columns: - using the apply function - using a for loop - using a while loop

Write R commands to address each question. Only one_line command allowed. The shorter the better. 1. From a matrix of numeric, compute the proportion of columns with average value higher than 0. 2. From a matrix of numeric, print the name of the column with the highest value. 3. From a matrix of numeric, print the rows with only positive values.